1. Field of the Invention
The present invention relates to personal identification using biometrics and, more specifically, to a method for reconstructing a fingerprint image from a plurality of image frames captured using a swipe fingerprint sensor.
2. Related Art
Identification of individuals is an important issue for, e.g., law enforcement and security purposes, for area or device access control, and for identity fraud prevention. Biometric authentication, which is the science of verifying a person's identity based on personal characteristics (e.g., voice patterns, facial characteristics, fingerprints) has become an important tool for identifying individuals. Fingerprint authentication is often used for identification because of the relative ease, non-intrusiveness, and general public acceptance in acquiring fingerprints.
To address the need for rapid identification, fingerprint recognition systems have been developed that use electronic sensors to measure fingerprint ridges with a capacitive image capture system. One type of system captures the fingerprint as a single image. To use such sensors, an individual places a finger (any of the five manual digits) on the sensor element and holds the finger motionless until the system captures a good quality fingerprint image. But the cost of the capacitive fingerprint sensor is proportional to the sensor element area so there is a compelling need to minimize the sensor element area while at the same time ensuring that no relevant portion of the fingerprint is omitted during image capture. Further, large sensors require substantial area to install and are impracticable for many portable applications such as to verify the owner of portable electronic devices such as personal digital assistants or cellular telephones.
One way of reducing sensor size and cost is to rapidly sample data from a small area capacitive sensor element as a finger is moved (or “swiped”) over the sensor element. In these “swipe” sensors, the small area sensor element is generally wider but shorter than the fingerprint being imaged. Sampling generates a number of image frames as a finger is swiped over the sensor element, each frame being an image of a fraction of the fingerprint. The swipe sensor system then reconstructs the image frames into a complete fingerprint image.
While swipe fingerprint sensors are relatively inexpensive and are readily installed on most portable electronic devices, the amount of computation required to reconstruct the fingerprint image is much greater than the computation required to process a fingerprint captured as a single image. Swipe sensor computation requirements increase system costs and result in poor identification response time. Computational requirements are further increased because of variations in a digit's swipe speed and the need to accommodate various finger positions during the swipe as the system reconstructs a complete fingerprint image from the frames generated during the swipe. The sensor system must determine the finger's swipe speed so as to extract only the new portion of each succeeding frame as the system reconstructs the fingerprint image. Thus, for effective use for identification, current swipe sensors must be coupled to a robust computing system that is able to reconstruct the fingerprint image from the image frames in real or near-real time.
Another major drawback to the use of fingerprints for identification purposes arises from the difficulty in associating the captured image with a particular individual, especially in portable applications. The output of the sensor is typically compared to a library of known fingerprints using pattern recognition techniques. It is generally recognized that the core area of a fingerprint is the most reliable for identification purposes. With the image acquired by a large area sensor, the core area is consistently located in the general center of the image. With a swipe sensor, however, it is difficult to locate this core area. Unlike the image generated by a large area fingerprint sensor, the core location of the image reconstructed by a swipe sensor cannot be guaranteed to be located in the neighborhood of the image center due to the way a digit may be positioned as it is swiped over the sensor element.
For this reason, the use of fingerprint verification has been limited to stationary applications requiring a high degree of security and widespread adoption of fingerprint identification has been limited. What is needed is a fingerprint identification system that is inexpensive, that efficiently assembles swipe sensor frames into a fingerprint image, that locates the core area of the reconstructed fingerprint image, that authenticates the captured fingerprint image in real or near-real time, and that performs these tasks using the limited computing resources of portable electronic devices.